Practice Applications - 5.4.3 | 5. Supervised Learning – Advanced Algorithms | Data Science Advance
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5.4.3 - Applications

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Learning

Practice Questions

Test your understanding with targeted questions

Question 1 Easy

List one application of XGBoost in real-world scenarios.

💡 Hint: Think about where data scientists collaborate for challenges.

Question 2 Easy

What does XGBoost stand for?

💡 Hint: Focus on the 'X' part of XGBoost.

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

Question 1

Which application is NOT typically associated with XGBoost?

Kaggle Competitions
Healthcare Diagnosis
Social Media Marketing

💡 Hint: Think about the typical fields of data science.

Question 2

True or False: XGBoost is a type of neural network.

True
False

💡 Hint: Recall the differences between these types of algorithms.

1 more question available

Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

In a Kaggle competition, a team used XGBoost to predict customer churn in a subscription model. What steps would you recommend they take to optimize their model?

💡 Hint: Think about methods to improve model accuracy.

Challenge 2 Hard

Discuss how XGBoost can improve healthcare predictive analytics when dealing with high dimensional datasets.

💡 Hint: Consider how noise affects predictions.

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